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Orlichenko A, Qu G, Zhou Z, Liu A, Deng HW, Ding Z, Stephen JM, Wilson TW, Calhoun VD, Wang YP. A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.16.594528. [PMID: 38798580 PMCID: PMC11118390 DOI: 10.1101/2024.05.16.594528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Objective fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging. Methods We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevel-opmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP). Results We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity. Conclusion Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics. Significance Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.
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Isomura Y, Ohno M, Sudo S, Ono M, Kaminishi Y, Sumi Y, Yoshimura A, Fujii K, Akiyama K, Nishi E, Ozeki Y. Associations among plasma markers for N-methyl-d-aspartate receptor hypofunction, redox dysregulation, and insufficient myelination in patients with schizophrenia. Heliyon 2024; 10:e30193. [PMID: 38694089 PMCID: PMC11061757 DOI: 10.1016/j.heliyon.2024.e30193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 04/21/2024] [Accepted: 04/22/2024] [Indexed: 05/03/2024] Open
Abstract
Background Several hypotheses regarding the pathomechanisms of schizophrenia have been proposed. If schizophrenia is a unitary disease, then these pathological processes must be linked; however, if such links do not exist, schizophrenia may best be considered a group of disorders. Only a few studies have examined the relationships among these pathomechanisms. Herein, we examined the relationships among deficient myelination, NMDA receptor hypofunction, and metabolic dysregulation by measuring various plasma markers and examining their correlations. Methods Plasma samples were collected from 90 patients with schizophrenia and 68 healthy controls. Concentrations of nardilysin (N-arginine dibasic convertase, NRDC), a positive regulator of myelination, the NMDA receptor co-agonist d-serine and glycine, various additional amino acids related to NMDA receptor transmission (glutamate, glutamine, and l-serine), and homocysteine (Hcy), were measured. Concentrations were compared using independent samples t-test or logistic regression, and associations were evaluated using Pearson's correlation coefficients. Results Plasma glycine (t = 2.05, p = 0.042), l-serine (t = 2.25, p = 0.027), and homocysteine (t = 3.71, p < 0.001) concentrations were significantly higher in patients with schizophrenia compared to those in healthy controls. Logistic regression models using age, sex, smoking status, glutamine, glutamate, glycine, l-serine, d-serine, homocysteine, and NRDC as independent variables revealed significantly lower plasma d-serine (p = 0.024) and NRDC (p = 0.028), but significantly higher l-serine (p = 0.024) and homocysteine (p = 0.001) in patients with schizophrenia. Several unique correlations were found between NMDA receptor-related amino acids and NRDC in patients with schizophrenia compared to those in healthy controls, while no correlations were found between plasma homocysteine and other markers. No associations were found between plasma marker concentrations and disease status or cognitive function in patients with schizophrenia, except for a significant correlation between plasma glycine and full intelligence quotient. Conclusion Reduced myelination and NMDA receptor hypofunction may be related to pathological mechanisms in schizophrenia, while homocysteine dysregulation appears to be an independent pathological process. These results suggest that schizophrenia may be a group of disorders with unique or partially overlapping etiologies.
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Affiliation(s)
- Yoshiaki Isomura
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Mikiko Ohno
- Department of Pharmacology, Shiga University of Medical Science, Japan
| | - Satoshi Sudo
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Mayuko Ono
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Yuki Kaminishi
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Yukiyoshi Sumi
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Atsushi Yoshimura
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Kumiko Fujii
- Department of Psychiatry, Shiga University of Medical Science, Japan
| | - Kazufumi Akiyama
- Department of Biological Psychiatry and Neuroscience, Dokkyo Medical University School of Medicine, Japan
| | - Eiichiro Nishi
- Department of Pharmacology, Shiga University of Medical Science, Japan
| | - Yuji Ozeki
- Department of Psychiatry, Shiga University of Medical Science, Japan
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Orlichenko A, Qu G, Zhou Z, Liu A, Deng HW, Ding Z, Stephen JM, Wilson TW, Calhoun VD, Wang YP. A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds. ARXIV 2024:arXiv:2405.07977v1. [PMID: 38800653 PMCID: PMC11118598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Objective fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging. Methods We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevelopmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP). Results We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity. Conclusion Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics. Significance Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.
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Affiliation(s)
- Anton Orlichenko
- Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118
| | - Gang Qu
- Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118
| | - Ziyu Zhou
- Department of Computer Science, Tulane University, New Orleans, LA 70118
| | - Anqi Liu
- Center for Biomedical Informatics and Genomics, Tulane Integrated Institute of Data & Health Sciences, Tulane University, New Orleans, LA 70112
| | - Hong-Wen Deng
- Center for Biomedical Informatics and Genomics, Tulane Integrated Institute of Data & Health Sciences, Tulane University, New Orleans, LA 70112
| | - Zhengming Ding
- Department of Computer Science, Tulane University, New Orleans, LA 70118
| | | | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118
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Zhou C, Tang X, Yu M, Zhang H, Zhang X, Gao J, Zhang X, Chen J. Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia. Transl Psychiatry 2024; 14:124. [PMID: 38413564 PMCID: PMC10899251 DOI: 10.1038/s41398-024-02827-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.
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Affiliation(s)
- Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaowei Tang
- Department of Psychiatry, Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou, Jiangsu, China
| | - Miao Yu
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongying Zhang
- Department of Radiology, Subei People's Hospital of Jiangsu Province, Yangzhou University, Yangzhou, Jiangsu, China
| | - Xiaobin Zhang
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Ju Gao
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China.
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
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Tan Y, Zhu J, Hashimoto K. Autophagy-related gene model as a novel risk factor for schizophrenia. Transl Psychiatry 2024; 14:94. [PMID: 38351068 PMCID: PMC10864401 DOI: 10.1038/s41398-024-02767-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 01/03/2024] [Accepted: 01/10/2024] [Indexed: 02/16/2024] Open
Abstract
Autophagy, a cellular process where cells degrade and recycle their own components, has garnered attention for its potential role in psychiatric disorders, including schizophrenia (SCZ). This study aimed to construct and validate a new autophagy-related gene (ARG) risk model for SCZ. First, we analyzed differential expressions in the GSE38484 training set, identifying 4,754 differentially expressed genes (DEGs) between SCZ and control groups. Using the Human Autophagy Database (HADb) database, we cataloged 232 ARGs and pinpointed 80 autophagy-related DEGs (AR-DEGs) after intersecting them with DEGs. Subsequent analyses, including metascape gene annotation, pathway and process enrichment, and protein-protein interaction enrichment, were performed on the 80 AR-DEGs to delve deeper into their biological roles and associated molecular pathways. From this, we identified 34 candidate risk AR-DEGs (RAR-DEGs) and honed this list to final RAR-DEGs via a constructed and optimized logistic regression model. These genes include VAMP7, PTEN, WIPI2, PARP1, DNAJB9, SH3GLB1, ATF4, EIF4G1, EGFR, CDKN1A, CFLAR, FAS, BCL2L1 and BNIP3. Using these findings, we crafted a nomogram to predict SCZ risk for individual samples. In summary, our study offers deeper insights into SCZ's molecular pathogenesis and paves the way for innovative approaches in risk prediction, gene-targeted diagnosis, and community-based SCZ treatments.
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Affiliation(s)
- Yunfei Tan
- Center for Rehabilitation Medicine, Department of Psychiatry, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, 310014, Hangzhou, Zhejiang, China.
| | - Junpeng Zhu
- Center for Rehabilitation Medicine, Department of Psychiatry, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, 310014, Hangzhou, Zhejiang, China
| | - Kenji Hashimoto
- Division of Clinical Neuroscience, Chiba University Center for Forensic Mental Health, Chiba, 260-8670, Japan.
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6
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Mu E, Gurvich C, Kulkarni J. Estrogen and psychosis - a review and future directions. Arch Womens Ment Health 2024:10.1007/s00737-023-01409-x. [PMID: 38221595 DOI: 10.1007/s00737-023-01409-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 12/02/2023] [Indexed: 01/16/2024]
Abstract
The link between sex hormones and schizophrenia has been suspected for over a century; however, scientific evidence supporting the pharmacotherapeutic effects of exogenous estrogen has only started to emerge during the past three decades. Accumulating evidence from epidemiological and basic research suggests that estrogen has a protective effect in women vulnerable to schizophrenia. Such evidence has led multiple researchers to investigate the role of estrogen in schizophrenia and its use in treatment. This narrative review provides an overview of the effects of estrogen as well as summarizes the recent work regarding estrogen as a treatment for schizophrenia, particularly the use of new-generation selective estrogen receptor modulators.
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Affiliation(s)
- Eveline Mu
- HER Centre Australia, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
| | - Caroline Gurvich
- HER Centre Australia, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Jayashri Kulkarni
- HER Centre Australia, Central Clinical School, Monash University, Melbourne, Victoria, Australia
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7
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Türk Y, Devecioğlu İ, Küskün A, Öge C, Beyazyüz E, Albayrak Y. ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia. Psychiatry Res Neuroimaging 2023; 336:111726. [PMID: 37925764 DOI: 10.1016/j.pscychresns.2023.111726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 09/29/2023] [Accepted: 10/14/2023] [Indexed: 11/07/2023]
Abstract
We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.
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Affiliation(s)
- Yaşar Türk
- Radiology Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey; Radiology Department, İstanbul Health and Technology University Hospital, Kaptanpasa Mh., Darulaceze Cd., Sisli, İstanbul 34384, Turkey
| | - İsmail Devecioğlu
- Biomedical Engineering Department, Çorlu Faculty of Engineering, Tekirdağ Namık Kemal University, NKU Corlu Muhendislik Fakultesi, Silahtaraga Mh., Çorlu, Tekirdağ 59860, Turkey.
| | - Atakan Küskün
- Radiology Department, Medical Faculty, Kırklareli University, Cumhuriyet Mh., Kofcaz Yolu, Kayali Yerleskesi, Merkezi Derslikler 2, No 39/L, Merkez, Kırklareli, Turkey
| | - Cem Öge
- Psychiatry Department, Çorlu State Hospital, Zafer, Mah. Bülent Ecevit Blv. No:33, Çorlu, Tekirdağ 59850, Turkey
| | - Elmas Beyazyüz
- Psychiatry Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey
| | - Yakup Albayrak
- Psychiatry Department, Medical Faculty, Tekirdağ Namık Kemal University. Namik Kemal Mh., Kampus Cd., Suleymanpasa, Tekirdag 59100, Turkey
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8
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Fritze S, Brandt GA, Benedyk A, Moldavski A, Geiger-Primo LS, Andoh J, Volkmer S, Braun U, Kubera KM, Wolf RC, von der Goltz C, Schwarz E, Meyer-Lindenberg A, Tost H, Hirjak D. Psychomotor slowing in schizophrenia is associated with cortical thinning of primary motor cortex: A three cohort structural magnetic resonance imaging study. Eur Neuropsychopharmacol 2023; 77:53-66. [PMID: 37717350 DOI: 10.1016/j.euroneuro.2023.08.499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 08/17/2023] [Accepted: 08/28/2023] [Indexed: 09/19/2023]
Abstract
Psychomotor slowing (PS) is characterized by slowed movements and lower activity levels. PS is frequently observed in schizophrenia (SZ) and distressing because it impairs performance of everyday tasks and social activities. Studying brain topography contributing to PS in SZ can help to understand the underlying neurobiological mechanisms as well as help to develop more effective treatments that specifically target affected brain areas. Here, we conducted structural magnetic resonance imaging (sMRI) of three independent cohorts of right-handed SZ patients (SZ#1: n = 72, SZ#2: n = 37, SZ#3: n = 25) and age, gender and education matched healthy controls (HC) (HC#1: n = 40, HC#2: n = 37, HC#3: n = 38). PS severity in the three SZ cohorts was determined using the Positive and Negative Syndrome Scale (PANSS) item #G7 (motor retardation) and Trail-Making-Test B (TMT-B). FreeSurfer v7.2 was used for automated parcellation and segmentation of cortical and subcortical regions. SZ#1 patients showed reduced cortical thickness in right precentral gyrus (M1; p = 0.04; Benjamini-Hochberg [BH] corr.). In SZ#1, cortical thinning in right M1 was associated with PANSS item #G7 (p = 0.04; BH corr.) and TMT-B performance (p = 0.002; BH corr.). In SZ#1, we found a significant correlation between PANSS item #G7 and TMT-B (p = 0.005, ρ=0.326). In conclusion, PANSS G#7 and TMT-B might have a surrogate value for predicting PS in SZ. Cortical thinning of M1 rather than alterations of subcortical structures may point towards cortical pathomechanism underlying PS in SZ.
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Affiliation(s)
- Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Geva A Brandt
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Anastasia Benedyk
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Alexander Moldavski
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Lena S Geiger-Primo
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Jamila Andoh
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Sebastian Volkmer
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Urs Braun
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Robert C Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, University of Heidelberg, Heidelberg, Germany
| | | | - Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Research Group System Neuroscience in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
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Smucny J, Hanks TD, Lesh TA, Carter CS. Altered Associations Between Task Performance and Dorsolateral Prefrontal Cortex Activation During Cognitive Control in Schizophrenia. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1050-1057. [PMID: 37295646 DOI: 10.1016/j.bpsc.2023.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/11/2023] [Accepted: 05/31/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Dysfunctional cognitive control processes are now well understood to be core features of schizophrenia (SZ). A body of work suggests that the dorsolateral prefrontal cortex (DLPFC) plays a critical role in explaining cognitive control disruptions in SZ. Here, we examined relationships between DLPFC activation and drift rate (DR), a model-based performance measure that combines reaction time and accuracy, in people with SZ and healthy control (HC) participants. METHODS One hundred fifty-one people with recent-onset SZ spectrum disorders and 118 HC participants performed the AX-Continuous Performance Task during functional magnetic resonance imaging scanning. Proactive cognitive control-associated activation was extracted from left and right DLPFC regions of interest. Individual behavior was fit using a drift diffusion model, allowing DR to vary between task conditions. RESULTS Behaviorally, people with SZ showed significantly lower DRs than HC participants, particularly during high proactive control trial types ("B" trials). Recapitulating previous findings, the SZ group also demonstrated reduced cognitive control-associated DLPFC activation compared with HC participants. Furthermore, significant group differences were also observed in the relationship between left and right DLPFC activation with DR, such that positive relationships between DR and activation were found in HC participants but not in people with SZ. CONCLUSIONS These results suggest that DLPFC activation is less associated with cognitive control-related behavioral performance enhancements in SZ. Potential mechanisms and implications are discussed.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; Center for Neuroscience, University of California, Davis, Davis, California.
| | - Timothy D Hanks
- Center for Neuroscience, University of California, Davis, Davis, California; Department of Neurology, University of California, Davis, Davis, California
| | - Tyler A Lesh
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; Center for Neuroscience, University of California, Davis, Davis, California
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; Center for Neuroscience, University of California, Davis, Davis, California
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10
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Jing H, Zhang C, Yan H, Li X, Liang J, Liang W, Ou Y, Wu W, Guo H, Deng W, Xie G, Guo W. Deviant spontaneous neural activity as a potential early-response predictor for therapeutic interventions in patients with schizophrenia. Front Neurosci 2023; 17:1243168. [PMID: 37727324 PMCID: PMC10505796 DOI: 10.3389/fnins.2023.1243168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 08/18/2023] [Indexed: 09/21/2023] Open
Abstract
Objective Previous studies have established significant differences in the neuroimaging characteristics between healthy controls (HCs) and patients with schizophrenia (SCZ). However, the relationship between homotopic connectivity and clinical features in patients with SCZ is not yet fully understood. Furthermore, there are currently no established neuroimaging biomarkers available for the diagnosis of SCZ or for predicting early treatment response. The aim of this study is to investigate the association between regional homogeneity and specific clinical features in SCZ patients. Methods We conducted a longitudinal investigation involving 56 patients with SCZ and 51 HCs. The SCZ patients underwent a 3-month antipsychotic treatment. Resting-state functional magnetic resonance imaging (fMRI), regional homogeneity (ReHo), support vector machine (SVM), and support vector regression (SVR) were used for data acquisition and analysis. Results In comparison to HCs, individuals with SCZ demonstrated reduced ReHo values in the right postcentral/precentral gyrus, left postcentral/inferior parietal gyrus, left middle/inferior occipital gyrus, and right middle temporal/inferior occipital gyrus, and increased ReHo values in the right putamen. It is noteworthy that there was decreased ReHo values in the right inferior parietal gyrus after treatment compared to baseline data. Conclusion The observed decrease in ReHo values in the sensorimotor network and increase in ReHo values in the right putamen may represent distinctive neurobiological characteristics of patients with SCZ, as well as a potential neuroimaging biomarker for distinguishing between patients with SCZ and HCs. Furthermore, ReHo values in the sensorimotor network and right putamen may serve as predictive indicators for early treatment response in patients with SCZ.
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Affiliation(s)
- Huan Jing
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Chunguo Zhang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiaoling Li
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wenting Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Yangpan Ou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Weibin Wu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Huagui Guo
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wen Deng
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong, China
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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Qin X, Huang H, Liu Y, Zheng F, Zhou Y, Wang H. Increased Functional Connectivity Involving the Parahippocampal Gyrus in Patients with Schizophrenia during Theory of Mind Processing: A Psychophysiological Interaction Study. Brain Sci 2023; 13:brainsci13040692. [PMID: 37190657 DOI: 10.3390/brainsci13040692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/11/2023] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND Theory of Mind (ToM) is an ability to infer the mental state of others, which plays an important role during social events. Previous studies have shown that ToM deficits exist frequently in schizophrenia, which may result from abnormal activity in brain regions related to sociality. However, the interactions between brain regions during ToM processing in schizophrenia are still unclear. Therefore, in this study, we investigated functional connectivity during ToM processing in patients with schizophrenia, using functional magnetic resonance imaging (fMRI). METHODS A total of 36 patients with schizophrenia and 33 healthy controls were recruited to complete a ToM task from the Human Connectome Project (HCP) during fMRI scanning. Psychophysiological interaction (PPI) analysis was applied to explore functional connectivity. RESULTS Patients with schizophrenia were less accurate than healthy controls in judging social stimuli from non-social stimuli (Z = 2.31, p = 0.021), and displayed increased activity in the right inferior frontal gyrus and increased functional connectivity between the bilateral middle temporal gyrus and the ipsilateral parahippocampal gyrus during ToM processing (AlphaSim corrected p < 0.05). CONCLUSIONS Here, we showed that the brain regions related to sociality interact more with the parahippocampal gyrus in patients with schizophrenia during ToM processing, which may reflect a possible compensatory pathway of ToM deficits in schizophrenia. Our study provides a new idea for ToM deficits in schizophrenia, which could be helpful to better understand social cognition of schizophrenia.
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Affiliation(s)
- Xucong Qin
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huan Huang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Ying Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Fanfan Zheng
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yuan Zhou
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan 430060, China
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